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- Yao, W., Nandy, D., Lindsay, B., and Chiaromonte, F. (2019). Covariate Information Matrix for Sufficient Dimension Reduction. Journal of American Statistical Association, 114, 1752-1764. [pdf]
- Xiang, S., Yao, W., and Yang, G. (2019). An Overview of Semiparametric Extensions of Finite Mixture Models. Statistical Science, 34, 391-404. [pdf]
- Chen, Y. and Yao, W. (2017). Unified Inference for Sparse and Dense Longitudinal Data in Time-Varying Coefficient Models. Scandinavian Journal of Statistics, 44, 268-284. [pdf]
- Kurum, E., Li, R., Shiffman, S., and Yao, W. (2016). Time-Varying Coefficient Models for Joint Modeling Binary and Continuous Outcomes in Longitudinal Data. Statistica Sinica, 26, 979-1000. [pdf]
- Yao, W. and Li, L. (2014). A New Regression Model: Modal Linear Regression. Scandinavian Journal of Statistics, 41, 656-671. [pdf]
- Huang, M., Li, R., and Huang, H., and Yao, W. (2014). Estimating Mixture of Gaussian Processes by Kernel Smoothing. Journal of Business and Economics Statistics, 32, 259-270. [pdf]
- Yao, W. and Li, R. (2013). New Local Estimation Procedure for Nonparametric Regression Function of Longitudinal Data. Journal of the Royal Statistical Society, Ser B., 75, 123-138. [pdf]
- Huang, M. and Yao, W. (2012). Mixture of Regression Models with Varying Mixing Proportions: A Semiparametric Approach. Journal of American Statistical Association, 107, 711-724. [pdf]
- Yao, W., Lindsay, B. G., and Li, R. (2012). Local modal regression. Journal of Nonparametric Statistics, 24, 647-663. The winner of The Journal of Nonparametric Statistics Best Paper Award in 2015. [pdf]
- Yao, W. (2012). Model Based Labeling for Mixture Models. Statistics and Computing, 22, 337-347. [pdf]
- Wang, Q. and Yao, W. (2012). An Adaptive Estimation of MAVE. Journal of Multivariate Data Analysis, 104, 88-100. [pdf]
- Cao, J. and Yao, W. (2012). Semiparametric Mixture of Binomial Regression with a Degenerate Component. Statistica Sinica, 22, 27-46. [pdf]
- Yao, W. (2010). A Profile Likelihood Method for Normal Mixture with Unequal
Variance. Journal of Statistical Planning and Inference, 140, 2089-2098. [pdf], Matlab code.
- Yao, W. and Lindsay, B. G. (2009). Bayesian Mixture Labeling by Highest Posterior Density.
Journal of American Statistical Association, 104, 758-767. [pdf], Matlab code.
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